Method and Device for Examining Value Documents for Irregularities

ABSTRACT

A means and method for checking a value document of at least one irregularity of at least one specified type, in which an ultrasound data record is captured which describes in locally resolved fashion at least one ultrasound property, a deviation data record is ascertained which describes in locally resolved fashion a deviation between the ultrasound data record and a model and is ascertained such that the deviation described thereby is minimal with respect to the model. The model comprises a model for the location dependence of the at least one ultrasound property of reference value documents of the specified value document type without irregularities of the at least one specified type, and using the deviation data record, it is checked whether an indication of an irregularity of the at least one type is present on the value document.

The present invention relates to a method for checking a value documentof a specified value document type for the presence of at least oneirregularity of at least one specified type, preferably at least oneadhesion, preferably an adhesive strip, and/or at least one creaseand/or a material removal, and means for carrying out the method.

In this context, value documents are understood to mean sheet-shapedobjects, which represent for example a monetary value or anauthorization and thus shall not be manufacturable at will byunauthorized persons. Hence, they have features that are not easilyproduced, in particular copied, whose presence is an indication ofauthenticity, i.e. of production by an authorized body. Importantexamples of such value documents are coupons, vouchers, checks and inparticular bank notes.

Such value documents may have irregularities or defects which may makethem appear unsuitable for a future usage or even are to be regarded asa, perhaps only weak, suspicion on the presence of a forgery.

An example of lacking suitability for a future usage can be, forexample, the presence of an adhesive strip on a value document, inparticular a bank note. Such adhesive strips are often employed torepair tears in the respective value document. The damaged valuedocument should hence be withdrawn from circulation, if possible.Another example may be that, in polymer bank notes, regions of an opaquelayer applied on the polymer substrate before or on printing chip off inthe course of time, so that a material removal is the result.

However, adhesive strips may also be used to connect parts of differentvalue documents with each other to produce a forgery.

For recognizing adhesive strips, a value document may be examined, forexample, by means of ultrasound transmission. With the aid of themeasuring data there can then be checked whether an indication of thepresence of an adhesive strip can be recognized.

A further form of irregularities which may impair the bank notes'fitness for circulation are creases and wrinkles. In U.S. Pat. No.6,595,060B2 there is described, for example, a method for thedetermination of structural inhomogeneities in sheet material, inparticular due to wrinkles or tears, in which ultrasound is employed. Inthe following, creases are understood to also be wrinkles.

However, such known methods suffer from the ultrasound transmission databeing very noisy, which is due to the kind of measurement and theproperties of certain types of value documents, and the recognition ofadhesive strips or creases or material removals thus being possiblydifficult. Likewise, the local resolution is substantially lower thanwith optical examinations.

The present invention is hence based on the object of stating a methodfor checking a value document of a specified value document type for thepresence of at least one irregularity of at least one specified type,preferably an adhesion, particularly preferably an adhesive strip,and/or a crease and/or an irregularity in the form of at least onematerial removal, which allows a good recognition of suchirregularities, and providing means for carrying out the method.

This object is achieved by the subject matters of the independentclaims.

In particular, the object is achieved by a method for checking a valuedocument of a specified value document type for the presence of at leastone irregularity of at least one specified type, in which an ultrasounddata record is captured which describes in locally resolved fashion atleast one ultrasound property, preferably the ultrasound transmission ofthe value document. A deviation data record is ascertained whichdescribes in locally resolved fashion a deviation between the ultrasounddata record and a model and is ascertained such that the deviationdescribed thereby is minimal with respect to the model, the modelcomprising a model for the location dependence of the at least oneultrasound property of reference value documents of the specified valuedocument type without irregularities of the at least one specified type.Using the deviation data record, it is checked whether an indication ofan irregularity of the at least one specified type is present on thevalue document.

The object is further achieved by an apparatus for checking a valuedocument of a specified value document type for the presence of at leastone irregularity of at least one specified type with an evaluationdevice which is configured to execute a method according to theinvention. It is in particular configured to capture an ultrasound datarecord which describes in locally resolved fashion at least oneultrasound property, preferably the ultrasound transmission, of thevalue document, to ascertain a deviation data record which describes inlocally resolved fashion a deviation between the ultrasound data recordand a model and is ascertained such that the deviation described therebyis minimal with respect to the model, the model comprising a model forthe location dependence of the at least one ultrasound property ofreference value documents of the specified value document type withoutirregularities of the at least one specified type, and, using thedeviation data record, to check whether an indication of an irregularityof the specified type is present on the value document.

For carrying out the method, the apparatus has the evaluation device.This may have a data processing device which, for example, may have acomputer or at least one processor and/or at least one FPGA forprocessing the ultrasound data. The evaluation device may have a memoryin which a computer program is stored, so that the evaluation device,preferably the data processing device executes the method according tothe invention upon the execution of the computer program.

The object is hence also achieved by a computer program for execution bymeans of a data processing device, which has program code, upon theexecution of which the data processing device executes a methodaccording to the invention.

The object is further achieved by a physical data carrier which isreadable by means of a data processing device and on which a computerprogram according to the invention is stored.

The method and the apparatus relate to the check of a value document ofa specified value document type. The value document types may be givenin that in each case different models within the meaning of theinvention are necessary for them. In the case of value documents in theform of bank notes, a value document type may be given in particular bythe currency and the face value or denomination and, where applicable,the series or issue. The value document type of bank notes may also bedetermined in more detail with respect to the subsequent processing,namely by the orientation of the bank notes. The orientation here isunderstood to mean one of the four possible positions of the bank noteupon the capture of the ultrasound property, which positions maytransition into each other by a rotation around the longitudinal centeraxis and/or transverse center axis of the bank note.

The value documents are checked for the presence of at least oneirregularity of at least one specified type. The reference valuedocuments preferably do not have irregularities of the at least onespecified type which is checked.

An irregularity of at least one specified type is understood to mean,depending on the embodiment, an irregularity of only one specified typeor an irregularity of one of several specified types. In particular, thefollowing types may be considered alone or in combination.

Thus, irregularities of the at least one specified type may compriseirregularities of the type of an adhesion, preferably an adhesive stripand/or irregularities of the crease type. The type of the irregularitymay thus preferably be an adhesion, preferably an adhesive strip.Adhesions are understood to mean any elements which are connected withthe value document and are arranged at least partially on its surface.These may be, for example, regions with an ink of enough weight per unitarea or in particular also adhesive strips or other adhesive elementsglued onto the value document. Irregularities of this type are alsoreferred to as irregularities in the form of adhesions. The type of theirregularity may thus preferably also be a crease. A crease within theframework of the invention is understood to mean only such a creasewhich leads to a change of the ultrasound property recognizable by asensor. Irregularities of this type are also referred to asirregularities in the form of creases.

Irregularities of the adhesion and/or crease types are irregularities inthe form of adhesions and/or creases.

The type of the irregularity may preferably also be a material removal.The irregularity of this type is also be referred to as irregularity inthe form of a material removal. Material removals within the frameworkof the present invention are value document regions whose weight perunit area is reduced compared with corresponding regions of specifiedreference value documents of the specified value document type. Inparticular in the case of value documents having a polymer layer with anopaque layer applied thereon these regions can be regions in which theopaque layer is damaged, in particular is no longer present.

Preferably, the check is effected either only for the presence of atleast one irregularity in the form of an adhesion and/or a crease oronly for the presence of at least one irregularity in the form of amaterial removal. In the first case, the reference value documents thenpreferably merely need not have any irregularities in the form ofadhesive strips and creases, in the second case merely not anyirregularities in the form of material removals. Particularlypreferably, the check either is only effected for the presence of atleast one irregularity in the form of an adhesion or only for thepresence of at least one irregularity in the form of a crease or onlyfor the presence of at least one irregularity in the form of a materialremoval. In the first case, the reference value documents thenpreferably merely need not have any irregularities in the form ofadhesive strips, in the second case merely not any irregularities in theform of creases and in the third case merely not any irregularities inthe form of material removals.

For the check, an ultrasound data record is captured, which describes inlocally resolved fashion at least one ultrasound property of the valuedocument. The ultrasound property may be, for example, phase changesupon remission and/or transmission of ultrasound at or through the valuedocument or preferably the remissivity or the remission or remissionintensity or remission amplitude for ultrasound in a specified frequencyregion or the transmissivity or the transmission or transmissionintensity or transmission amplitude for ultrasound in a specifiedfrequency region. Ultrasound is understood here to mean sound withfrequencies in a region between 50 kHz and 2 MHz, preferably between 50kHz and 1 MHz, particularly preferably between 100 kHz and 1 MHz. Veryparticularly preferably, ultrasound with frequencies in the regionbetween 100 kHz and 500 kHz is employed.

The ultrasound data record describes the ultrasound property in locallyresolved fashion, that is, that for a plurality of measuring dots on thevalue document there are given ultrasound data corresponding to therespective place of the measuring dot and describing the ultrasoundproperty. The places may be explicitly indicated in the ultrasound datarecord here. However, it is also possible that the place is implicitlygiven by the arrangement of the ultrasound data in the ultrasound datarecord; in this case a rule is specified as to which places correspondto which ultrasound data in the ultrasound data record. Preferably,ultrasound data are captured for places which are distributed over thewhole value document. The places may be distributed irregularly, butpreferably they are distributed regularly, particularly preferably onthe node of a rectangle grid.

In principle, it is sufficient that the ultrasound data record is merelycaptured, for example read or received. The apparatus, preferably theevaluation device, may have, for this purpose, a suitable interface viawhich ultrasound data records can be captured.

However, in the method, the ultrasound data are preferably captured bymeans of an ultrasound sensor. In the apparatus it is then preferred,that the apparatus further has an ultrasound sensor for the locallyresolved measurement of the at least one ultrasound property of a valuedocument and formation of an ultrasound data record for the valuedocument, and that the evaluation device is coupled to the ultrasoundsensor via a signal connection and is configured to capture anultrasound data record of the ultrasound sensor as an ultrasound datarecord.

The ultrasound sensor may be configured for measuring the ultrasoundproperty of a value document which is at rest relative to the ultrasoundsensor. However, it is preferred that the ultrasound sensor isconfigured such that it measures the ultrasound property of the valuedocument during a motion of the value document, in particular during atransport of the value document past or through the ultrasound sensor.For this purpose, a transport device may be provided which transportsthe value document at a specified transport speed past or through theultrasound sensor.

The ultrasound sensor may preferably have several ultrasound transducerswhich may serve as ultrasound transmitters and/or ultrasound receivers.In particular, the ultrasound sensor may be a transmission ultrasoundsensor. Upon the formation of the ultrasound data record, the measuringsignals of the ultrasound transducers acting as ultrasound receivers maybe subjected to a preprocessing.

The captured ultrasound data record is then compared to the model. Moreprecisely, from the captured ultrasound data record there is ascertainedthe deviation data record which describes in locally resolved fashion adeviation between the captured ultrasound data record and the model. Forthis purpose, for the value document type there is specified the modelwhich comprises or is a model for the location dependence of the atleast one ultrasound property of reference value documents of thespecified type without irregularities of the at least one specifiedtype, preferably depending on the at least one specified type withoutadhesions and/or creases and/or material removals. The model hencedescribes approximatively the at least one ultrasound property of thereference value documents in locally resolved fashion. The modeldescribes the location dependence of the ultrasound property or thelocation-dependent ultrasound property of the reference value documentsby way of a model, thus need not render the location dependence of theultrasound property exactly, but, as the term “model” implies, onlyapproximatively, i.e. with certain errors. The errors, however, as theterm “model” implies, may not become arbitrarily large. The personskilled in the art chooses the allowed error or accuracy of the model insuch a way that the method according to the invention works in such away that it meets the requirements in particular in view of embodimentspeed and recognition accuracy.

In a simple case, the model needs to define only one model data recordwhich is obtainable, for example, by an averaging of referenceultrasound data records for value documents of the specified valuedocument type without irregularities of the at least one specified type,preferably depending on the at least one specified type without in theform of adhesions and/or creases and/or material removals.

In the method it is preferred, however, that the model defines aplurality of model data records differing from each other, whichdescribe the at least one ultrasound property in location-dependentfashion. In the apparatus it is accordingly preferred that the modeldefines a plurality of model data records differing from each other,which describe the at least one ultrasound property inlocation-dependent fashion. In this way, there can be modelledparticularly well variations in the ultrasound properties of the valuedocuments of the specified value document type, which are caused by thevalue document type and/or the manufacturing, but not by later attachedadhesions or later generated creases or later effected materialremovals. This may substantially increase the selectivity of the method.

The model may be specified by the model data records being explicitlyspecified. Preferably, however, the model is specified by modelparameters and an instruction for ascertaining model data records usingthe model parameters being at least given such that the deviation datarecord can be ascertained.

The deviation data record is ascertained such that the deviation withrespect to the model, i.e. from the model, described thereby, isminimal. For ascertaining the quantity of a deviation between anultrasound data record and the model, a deviation measure can bespecified which is chosen in dependence on the model and therepresentation of the ultrasound data records. A deviation is minimalwhen the deviation measure is minimal. Preferably, the deviation betweenthe ultrasound data record and the model is a deviation between theultrasound data record and one of the model data records.

This deviation data record will include deviations, besides thedeviations which may occur between the model and value documents withoutirregularities due to the usage of the model, which are caused byirregularities of the at least one specified type, preferably adhesionsand/or creases and/or material removals. By using a model whichdescribes the location dependence of the ultrasound property deviationsare more clearly recognizable due to irregularities of the at least onespecified type, preferably adhesions and/or creases and/or materialremovals. In particular when for reference value documents there isemployed a model which defines a plurality of model data records,variations of the ultrasound property caused by fluctuations in theproperties of value documents of the specified value document type, inthe case of bank notes, for example, the position of watermarks and/orsecurity threads, can be separated from such caused by adhesions orcreases or material removals. This facilitates the check in thesubsequent step.

Therein, using the deviation data record, it is checked whether or notan indication of an irregularity of the at least one specified type,preferably in the form of at least one adhesion, preferably an adhesivestrip, and/or a crease and/or at least one irregularity in the form of amaterial removal, is present on the value document. In this way, a veryhigh accuracy or reliability of the recognition of irregularities of theat least one specified type, preferably adhesions and/or creases and/orof material removals, may be achieved, even when the influence of therespective irregularities, for example adhesions or creases or of thematerial removals on the at least one ultrasound property, is not verylarge. There also results a very high reliability in the recognition.

As a result of the check, a datum may be stored or a signal be formed,which describes whether or not the mentioned indication is present. Sucha datum or signal may be employed directly or, optionally, in connectionwith other data and/or signals describing indications of the presence ofother irregularities, for sorting the value document.

In principle, the model data records do not need to be structured ordefined like the ultrasound data records, as long as the deviationmeasure allows ascertaining a minimal deviation. Preferably, however,the ultrasound data records respectively include ultrasound data for anumber N of places which is specified for the value document type, whichdata respectively describe the at least one ultrasound property for therespective places. Accordingly and preferably, the model data recordsthen respectively include model data for the at least one ultrasoundproperty for the specified number N of places. This permits a simplecomparison of the ultrasound data and the model data for every place.This allows in particular a simple formulation of a distance measure,for example, as a sum of the squared differences between the ultrasounddata and the model data over the given places. When representing theultrasound data records and the model data records by vectors, thedeviation measure may be given, for example, by the Euclidean or L2 normof the difference vector which is given by the difference from thevector representing the ultrasound data record and the vector describingthe model data record.

Preferably, in the method, the ultrasound data records respectivelyinclude ultrasound data for a number N of places which is specified forthe value document type, which data respectively describe the at leastone ultrasound property for the respective places, and the model datarecords respectively include model data for the at least one ultrasoundproperty for the specified number N of places. Accordingly, in theapparatus, preferably the ultrasound data records respectively includeultrasound data for a number N of places which is specified for thevalue document type, which data respectively describe the at least oneultrasound property for the respective places, and the model datarecords respectively include model data for the at least one ultrasoundproperty for the specified number N of places. The model data recordsthen lie preferably in a specified partial region of an N-dimensionalspace of possible ultrasound data. Such a model thus provides a verylarge number of model data records. In addition, the model data recordsmay form a continuum, which may greatly simplify the ascertainment ofthe deviation data record, because the results of minimization methodscan be employed.

Preferably, in the method, the partial region is specified such thatmodel data records are representable, in case the ultrasound data recordand the model data records are represented as vectors of the samedimension, by a sum of a mean vector and a linear combination of atleast five, preferably ten, specified partial-region vectors.Accordingly, in the apparatus, preferably the partial region can bespecified such that model data records are representable, in case theultrasound data record and the model data records are represented asvectors of the same dimension, by a sum of a mean vector and a linearcombination of at least five, preferably ten, specified partial-regionvectors. With this representation, the same components of the vector forthe ultrasound data record and for the model data record respectivelycorrespond to the same place. Furthermore, the partial-region vectorsare linearly independent. This embodiment has—inter alia—the advantagethat for deviation criteria like the length or norm of the difference ofthe vectors corresponding to the ultrasound data record or to the modeldata record, the deviation data record can be easily ascertained withminimal deviation without the execution of numerical minimizationmethods.

Preferably, the partial-region vectors are chosen such that they areorthogonal to each other.

Furthermore, preferably the mean vector and the partial-region vectorsare obtainable or preferably obtained by an analysis of referenceultrasound data records for specified reference value documents of thespecified value document type without irregularities of the at least onespecified type, i.e. preferably depending on the at least one specifiedtype without adhesions or creases and material removals. As referencevalue documents of the specified value document type there arepreferably employed reference value documents of different states, forexample, freshly printed and used, preferably multiply circulated valuedocuments.

Particularly preferably, the analysis comprises a main componentanalysis, the mean value ascertained upon the main component analysiscorresponding to the mean vector and the main components ascertainedupon the main component analysis corresponding to the partial-regionvectors. In this way, there can be obtained in a simple and systematicmanner a model which describes the most important variations of thelocation-dependent ultrasound property but remains relatively simple.The person skilled in the art can chose the number of the employedpartial-region vectors or main components in dependence on theproperties of the value documents of the specified value document type,the resources available for carrying out the method, and the requiredexecution speed.

Furthermore, it is preferred that the model has a statistical modeldistribution which describes a probability for the model data records.In particular, in case the main component analysis is employed, thestatistical model distribution may correspond to a main components'distribution ascertained according to the main component analysis. Thedistribution is understood here to mean the probability density. Thiscan be employed, where applicable, in the following method step.

The check whether an indication of an irregularity of the at least onespecified type, preferably of an irregularity in the form of at leastone adhesion, preferably an adhesive strip, and/or at least one creaseand/or at least one irregularity in the form of at least one materialremoval, is present on the value document, may basically be carried outarbitrarily, but in a suitable manner using the deviation data record.Upon the check there may be employed parameters, which may be gained bychecking training value documents of the specified value document typewithout irregularities of the at least one specified type, preferably inthe form of at least one adhesion, for example an adhesive strip, and/orat least one crease and/or without irregularities in the form of atleast one material removal, and those having such irregularities of theat least one specified type, or the use of the ultrasound training datarecords captured for such training value documents.

However, preferably, for the deviation data record there is ascertained,using the deviation data record, at least one feature, and upon checkingwhether an indication of an irregularity of the at least one specifiedtype, preferably an irregularity in the form of at least one adhesion,preferably an adhesive strip, and/or at least one crease and/or anirregularity in the form of at least one material removal is present onthe value document, the at least one feature is employed. The at leastone feature is a feature representable by a feature function at least ofsome data of the deviation data record, so that with an irregularity ofthe at least one specified type, preferably an irregularity in the formof an adhesion, preferably an adhesive strip, and/or a crease and/or anirregularity in the form of a material removal, the feature functionassumes a significant value. Preferably, several different such featuresare ascertained and employed upon the checking.

The choice of the features is only limited by their suitability forchecking. In particular, preferably the following alternatives may beemployed.

According to a preferred alternative, the feature or one of the featuresmay relate to or describe the probability that the captured ultrasounddata record or the deviation data record or the model data recordcorresponding to the deviation data record occurs according to themodel. In the two first cases, the probability corresponds to theprobability that the ultrasound data record corresponds to a valuedocument of the specified value document type without irregularities ofthe at least one specified type, preferably depending on the at leastone specified type without irregularities in the form of at least oneadhesion or crease or without irregularities in the form of at least onematerial removal; in the last case, when employing the probability ofthe model data record, the probability may correspond to the probabilitythat the ultrasound data record occurs under the condition that thevalue document has no irregularity of the at least one specified type,preferably, depending on the at least one specified type, noirregularity in the form of at least one adhesion, for example anadhesive strip, or one crease or no irregularity in the form of at leastone material removal.

According to a further preferred alternative, the feature or one of thefeatures may describe or represent the quantity of the deviationdescribed by the deviation data record. The quantity is understood hereto mean the whole quantity of the deviation, where applicable,normalized to for example the number of the ultrasound data of theultrasound data records. With a representation as a vector, as a measurefor the quantity there can be employed, for example, the norm or lengthor a function of these quantities.

According to another preferred alternative, the feature or one of thefeatures may represent a measure for the magnitude of the deviations atthose places at which the deviation data of the deviation data recordindicate an irregularity of the at least one specified type, preferablydepending on the at least one specified type either in the form of atleast one adhesion and/or a crease or to an irregularity in the form ofat least one material removal. The magnitude of the deviations may begiven, for example, by the mean value and/or the variance of thedeviations, which indicate the mentioned irregularity. The magnitude isascertained for the feature in dependence on the at least one specifiedtype, preferably either for irregularities in the form of at least oneadhesion and/or a crease or for irregularities in the form of at leastone material removal, because the respective deviation data may havedifferent signs. Thus, an adhesion typically reduces the ultrasoundtransmission, so that depending on the representation of the deviationdata record, the deviation given by the model data record or thedeviation datum for a place with adhesion will be smaller than therespective captured ultrasound transmission for the same place; thedeviation datum for the place is then smaller than zero. The sameapplies to creases. With a material removal, however, the relations arevice versa, there results the opposite sign for the deviation datum.

According to a still further alternative, the feature or one of thefeatures may relate to or represent or describe a measure for places,for which the deviation data of the deviation data record indicate anirregularity of the at least one specified type, preferably anirregularity in the form of either at least one adhesion and/or a creaseor an irregularity of at least one material removal, occurring spatiallycumulated and preferably neighboring, and that preferably uponascertaining the measure also the quantities of the deviations are takeninto account. The measure may in particular depend on an energyfunction. An energy function is preferably understood here to mean afunction which comprises a sum of contributions which respectivelyinclude products of deviation data at different places, weighted with aweighting factor depending on the distance of the places; in doing so,there are taken into account preferably only deviation data whichindicate an irregularity of the at least one specified type, preferablyan irregularity in the form of either at least one adhesion, preferablyan adhesive strip, and/or a crease or an irregularity in the form of amaterial removal. In this manner, there can be taken into accountwhether the deviations are present only sporadically scattered and,hence, rather indicate measurement errors or whether the deviations aredistributed extensively, as it is to be expected for irregularities ofthe at least one specified type, preferably irregularities in the formof adhesions and/or creases or material removals.

A still further preferred alternative relates in particular to the casethat the irregularities of the at least one specified type, for exampleirregularities in the form of adhesions and/or creases or of materialremovals, typically have a specified form, for example in the case ofadhesive strips are strip-shaped and straight. In the method, preferablythe feature or one of the features may relate to or represent a measurefor the presence of deviations at places for which the deviation data ofthe deviation data record indicate an irregularity of the at least onespecified type, for example an irregularity in the form of an adhesionand/or crease or an irregularity in the form of a material removal,along a line of a specified form, preferably a straight line.Preferably, for ascertaining the feature there can be carried out aHough transformation or a Fast-Hough transformation or a modification ofone of these transformations for the deviation data of the deviationdata record which correspond to places for which the deviation data ofthe deviation data record indicate an irregularity of the at least onespecified type, for example an irregularity in the form of an adhesionand/or crease or to an irregularity in the form of a material removal.This alternative allows a particularly clear recognition of adhesivestrips which mostly are affixed straight.

A still further preferred alternative provides that for deviation dataindicating an irregularity of the at least one specified type, forexample an irregularity in the form of an adhesion and/or a crease or amaterial removal, a blob analysis is carried out and a property of theascertained blobs or areas corresponding to these, preferably the numberof places therein, particularly preferably only the number of places inthe largest blob or area corresponding thereto, is employed as afeature. A blob designates here a set of places which form a coherentarea and whose deviation data indicate an irregularity of the at leastone specified type, for example an irregularity in the form of anadhesion and/or crease or an irregularity in the form of a materialremoval.

In a particularly preferably development, as a feature there can beascertained a measure for the places in the ascertained setsrespectively lying within a form enclosing the places as close aspossible. For example, the ratio from the number of places and the areagiven by the form may be employed.

Upon checking whether an indication of an irregularity of the at leastone specified type, for example an irregularity in the form of at leastone adhesion, preferably an adhesive strip, and/or a crease and/or on anirregularity in the form of a material removal is present on the valuedocument, there may preferably be carried out a classification by meansof a support vector machine using the at least one feature or thefeatures. This has the advantage, that a more accurate classification ismade possible.

It is then particularly preferred that upon checking there isascertained a probability that for the specified ultrasound data recordthere was ascertained an irregularity of the at least one specifiedtype, for example an irregularity in the form of an adhesion, preferablyan adhesive strip, or a crease or a material removal. For ascertainingthis probability there may be employed parameters which areascertainable using ultrasound training data records which were capturedfor training value documents of the specified value document havingirregularities of the at least one specified type, for example anirregularity in the form of at least one adhesion, preferably anadhesive strip, or at least one crease or with irregularities in theform of at least one material removal, and for training value documentsof the specified value document type without irregularities of the atleast one specified type, preferably depending on the at least onespecified type, irregularities in the form of at least one adhesion,preferably an adhesive strip, or at least one crease or at least onematerial removal.

The embodiments discussed hereinbefore do not only apply to the method,even if they are described only in connection with the method, butaccordingly also for the apparatus or the computer program.

Subject matter of the invention is further an apparatus for processingvalue documents with a feeding device for feeding value documents, anoutput device for receiving processed, i.e. sorted value documents, anda transport device for transporting singled value documents from thefeeding device to the output device. The apparatus further comprises anapparatus according to the invention for checking the transported valuedocuments.

For ascertaining the parameter employed upon checking there is mostlyrequired a large number of ultrasound training data records for valuedocuments of the specified type having an irregularity of the at leastone specified type, preferably an irregularity in the form of anadhesion and/or a crease or a material removal. However, those are notalways available and may have to be prepared.

The subject matter of the invention is hence also a method forgenerating ultrasound training data for adapting parameters of a methodfor checking a value document of a specified value document type for thepresence of at least one irregularity of at least one specified type,preferably an irregularity in the form of at least one adhesion,preferably an adhesive strip, and/or at least one crease and/or at leastone irregularity in the form of at least one material removal, in whichfor specified reference value documents of the specified value documenttype there are captured ultrasound data records which respectivelydescribe in locally resolved fashion at least one ultrasound property,preferably the ultrasound transmission, of the respective referencevalue document, the specified reference value documents not having anirregularity of the at least one specified type, preferably, dependingon the at least one specified type, an irregularity in the form of atleast one adhesion, preferably an adhesive strip, and/or at least onecrease and/or an irregularity in the form of at least one materialremoval. At least some of the ultrasound data records are stored asultrasound training data records. Furthermore, from at least some of theultrasound data records, which may or may not be included at leastpartially in the already stored ultrasound training data records, thereare generated further ultrasound training data records, by changing theultrasound data of the ultrasound data record for respectively givenplaces in such a way that the change corresponds to a given irregularityof the specified type, for example given adhesion or crease or a givenmaterial removal. These further ultrasound training data records arealso stored. Preferably, the parameters of the checking method areadapted using the ultrasound training data records.

For the capture of the ultrasound data records, the explanationsregarding the checking method apply accordingly here. This procedure hasthe great advantage that a very large number of ultrasound training datarecords can be easily produced without great effort. The change can beeasily executed by means of a data processing device.

It is preferred here that upon the generation of one of the furtherultrasound training data records the places are respectively given suchthat the form and/or the position of the irregularity of the specifiedtype, for example the adhesion or crease or the material removal, ischosen from a specified set of possible forms or positions. Inparticular, the positions and, where applicable, also the forms may berandomly chosen within the specified region.

Furthermore, it is preferred, that upon the generation of one of thefurther ultrasound training data records or of one of the furtherultrasound training data records, the quantity of the change by theirregularity of the specified type, for example, by the given adhesionor crease or the given material removal, is chosen from a specifiedregion or a specified set. The set of the changes may comprise, forexample, the changes by adhesive strips of different specifiedthicknesses.

The explanations regarding the checking method apply accordingly to thetypes of irregularity.

The invention will hereinafter be explained further by way of examplewith reference to the drawings, in which

FIG. 1 shows a schematic view of a value-document processing apparatusin the form of a bank-note sorting apparatus,

FIG. 2 shows a schematic representation of a transmission ultrasoundsensor of the apparatus in FIG. 1,

FIG. 3 shows a schematic representation of an arrangement of ultrasonictransducers of the transmission ultrasound sensor in FIG. 2, which serveas ultrasound transmitters, in a plane parallel with a transportdirection of the value documents,

FIG. 4 shows a schematic representation of a value document withwatermark, security thread and an adhesion in the form of an adhesivestrip,

FIG. 5 shows a simplified flowchart of a first embodiment of a methodfor checking value documents for the presence of an irregularity in theform of an adhesion or crease, which can be carried out by means of theapparatus in FIG. 1,

FIG. 6 shows a simplified flowchart of a second embodiment of a methodfor checking value documents for the presence of an irregularity in theform of an adhesion or crease, which can be carried out by means of theapparatus in FIG. 1, and

FIG. 7 shows a simplified flowchart of a third embodiment of a methodfor checking value documents for the presence of an irregularity in theform of an adhesion or crease, which can be carried out by means of theapparatus in FIG. 1.

A value-document processing apparatus 10 in FIG. 1, in the example anapparatus for processing value documents 12 in the form of bank notes,is configured for sorting value documents in dependence on therecognition of the authenticity and of the state of processed valuedocuments. The components of the apparatus described in the followingare arranged in a housing (not shown) of the apparatus or are held atthis, unless they are referred to as external.

The apparatus has a feeding device 14 for feeding value documents, anoutput device 16 for receiving processed, i.e. sorted value documents,and a transport device 18 for transporting singled value documents fromthe feeding device 14 to the output device 16.

The feeding device 14 comprises, in the example, an input pocket 20 fora value-document stack and a singler 22 for singling value documentsfrom the value-document stack in the input pocket 20 and for feeding thesingled value documents to the transport device 18.

The output device 16 has, in the example, three output portions 24, 25and 26 into which processed value documents can be sorted, sortedaccording to the result of the processing. In the example, each of theportions has a stack pocket and a stacking wheel (not shown) by means ofwhich fed value documents can be deposited in the stack pocket.

The transport device 18 has at least two, in the example three, branches28, 29 and 30 at whose ends one of the output portions 24 or 25 or 26 isdisposed respectively, and, at the branching points, gates 32 and 34controllable by actuating signals for feeding value documents to thebranches 28 to 30 and thus to the output portions 24 to 26 in dependenceon actuating signals.

On a transport path 36, defined by the transport device 18, between thefeeding device 14, in the example more precisely the singler 22, and thefirst gate 32 after the singler 22 in the transport direction there isdisposed a sensor device 38 which measures physical properties of thevalue documents when value documents are being transported past, andforms sensor signals representing the measurement results. In thisexample, the sensor device 38 has three sensors, namely an opticalremission sensor 40 which captures a remission color image and aremission IR image of the value document, an optical transmission sensor42 which captures a transmission color image and a transmission IR imageof the value document, and a transmission ultrasound sensor 44 whichcaptures or measures the ultrasound transmission of the value documentin locally resolved fashion as an ultrasound property and willhereinafter only be referred to as an ultrasound sensor for simplicity'ssake. The sensor signals formed by the sensors correspond to measurementdata or raw data of the sensors, which, depending on the sensor, couldalready have been subjected to a correction, for example in dependenceon calibrating data and/or noise properties.

For capturing and displaying operating data, the value-documentprocessing apparatus 10 has an input/output device 46. The input/outputdevice 46 is implemented, in the example, by a touch-sensitive displaydevice (“touch screen”). In other embodiment examples, it may comprise,for example, a keyboard and a display device, for example an LCDdisplay.

A control and evaluation device 48 is connected via signal connectionsto the sensor device 38, the input/output device 46 and the transportdevice 18, in particular the gates 32 and 34.

The control and evaluation device 48 forms a data processing device andhas, besides corresponding data interfaces (not shown in the Figures)for the sensor device 38 or their sensors, a processor 50 and a memory52 connected to the processor 50, in which at least one computer programwith program code is stored, upon the execution of which the control andevaluation device 48 or the processor 50 controls the apparatusaccording to the properties of the value documents. Thus, in itsfunction as an evaluation device it may evaluate the sensor signals, inparticular for ascertaining an authenticity class and/or a state classof a processed value document, and in its function as a control deviceit may drive the transport device 18 in accordance with the evaluationand optionally store the measurement data. In other embodiment examplesthere may also be provided an evaluation device separate from thecontrol device, which is connected via interfaces to the sensors of thesensor device 38, on the one hand, and the control device, on the otherhand. The evaluation device is then configured for analysing the sensorsignals and delivers the respective result to the control device whichdrives the transport device. The evaluation operations described in thefollowing may then be carried out by the evaluation device alone.

Further, the control and evaluation device 48 drives the input/outputdevice 46 such, among other things, that it displays operating data, andcaptures via these operating data which correspond to inputs of anoperator.

In operation, value documents are singled from the feeding device andtransported past or through the sensor device 38. The sensor device 38captures or measures physical properties of the value documentrespectively transported past or through it and forms sensor signals ormeasurement data which describe the measurement values for the physicalproperties. The control and evaluation device 48 classifies the valuedocument in dependence on the sensor signals of the sensor device 38 fora value document and on classification parameters stored in theevaluation device into one of specified authenticity and/or stateclasses, and by emitting actuating signals drives the transport device18, here more precisely the gates 32 or 34, such that the value documentis output, corresponding to its class ascertained upon theclassification, into an output portion of the output device 16 which isassociated with the class. The association with one of the specifiedauthenticity classes or the classification is effected here independence on at least one specified authenticity criterion.

Aspects of the formation and employment of ultrasound measurement dataare described in more detail in the following.

For the locally resolved capture of the ultrasound property, in theexample the ultrasound transmission, there serves the transmissionultrasound sensor 44 which is constructed in the example as follows (cf.FIGS. 2 and 3).

The ultrasound sensor 44 has several ultrasound transducers 54 arrangedtransverse to a transport direction T of the value documents 12 as wellas in parallel with this substantially in a plane in parallel with onealong the transport path 36 of the transported value document 12, drivenby the control and evaluation device 48 for emitting ultrasound pulsesonto the value document. These ultrasound transducers 54 thus serve asultrasound transmitters.

Opposite, relative to the transport path 36, to the ultrasoundtransducers or transmitters 54, the same number of ultrasoundtransducers 56 serving as ultrasound receivers is arranged in such a waythat these may receive ultrasound waves emitted by a value document 12transported along the transport path 36 and caused by acousticirradiation with ultrasound pulses of the ultrasound transmitters 54.The ultrasound transducers 56 are connected with the control andevaluation device 48 via interfaces (not shown in the Figures) andschematically shown signal connections.

Each of the ultrasound transmitters 54 has associated therewith one ofthe ultrasound receivers 56 such that there arises between these anultrasound path 58 extending at least approximatively orthogonal to avalue document 12 transported along the transport path 36, along whichpath an ultrasound pulse emitted by the respective ultrasoundtransmitter 54 runs to the ultrasound receiver 56 associated therewith.With every pair of ultrasound transmitters and ultrasound receiversassociated therewith or with every ultrasound path 58 in connection withthe control and evaluation device 48, a value for the ultrasoundtransmission of the value document 12 at the place acousticallyirradiated with ultrasound is thus ascertainable.

The ultrasound transducers 54 or 56 are configured such that they arewell suited for emitting or for receiving ultrasound pulses,respectively, with a duration in the region of about 30 μs in theexample and an ultrasound frequency, i.e. a frequency maximum of thespectrum of the ultrasound pulse, of about 400 kHz in the example.Further, they are dimensioned such that respectively one dot, i.e. scanregion, on a value document 12 transported along the transport path 36,which dot is acoustically irradiated with the ultrasound pulses uponacoustic irradiation, has a diameter of about 2 mm. Each of the scanregions has associated therewith the center of the scan region as aplace.

The ultrasound transmitters 54 and the ultrasound transducers 56respectively associated therewith, in the example are arranged offset intwo lines extending transverse to the transport direction. Theultrasound transducers of a respective line are arranged in the samedistances to each other and are operated simultaneously. The ultrasoundtransducers, however, are arranged in the lines such that the ultrasoundtransducers of the one of the lines transverse to the transportdirection are arranged offset opposite the ultrasound transducers of theother one of the lines.

The ultrasound transducers of all the lines are operated insynchronously pulsed fashion. When a value document 12 is transportedwith a constant, suitably specified speed through the ultrasound paths58, ultrasound transmission values are thus captured in specified timeintervals during the transport. In this embodiment example, the drivingis effected independent of a value document 12 entering the captureregion of the transmission ultrasound sensor 44. For suppressing anundesirable reception of ultrasound pulse echoes, the respectiveultrasound receiver for an ultrasound path may be switched on with adelay, relative to the time of the ultrasound transmitter emitting theultrasound pulse for the ultrasound path, by somewhat less than thepulse runtime for the ultrasound path and switched off before the doublepulse runtime since the emitting.

By offsetting the ultrasound transducers of the lines to each other andtheir alternate operation there arises a regular arrangement of scanregions or places on the value document 12, in the example anarrangement on a rectangle grid which is schematically shown by way ofexample in FIG. 4. The arrangement of the ultrasound transmitters andultrasound receivers 54 or 56 is chosen such that the distance ofconsecutive places in transport direction T is smaller than 1 cm,preferably smaller than 5 mm. In the example, the distance of mostadjacent places is about 3 mm, preferably 2 mm.

The ultrasound sensor 44 in the embodiment example has in particularmore than twenty-four pairs of ultrasound transmitters/receivers orultrasound paths 58, which are arranged such that the correspondingplaces have a distance between 3 and 4 mm.

For capturing the transmission values, i.e. the transmission, thecontrol and evaluation device 48 captures the sensor signals of theultrasound receivers 56 in constant time intervals, which reproduce theintensity or power of individual received ultrasound pulses as afunction of time and thus, because of the constant transport speed, alsoof place. On the basis of these signals the control and evaluationdevice 48 also ascertains the entry of the value document into thecapture region of the transmission ultrasound sensor 44. Thetransmission values are here simply given, assuming a basically constanttransmitting power of the ultrasound transmitters 54, by the receivedultrasound pulse energies. In other embodiment examples, however, it isalso possible to divide the received ultrasound pulse energies by aspecified or measured ultrasound pulse energy of transmitted pulses andto thus obtain normalized transmission values.

The ascertained ultrasound transmission values are stored associatedwith the places for which they were captured and form an ultrasound datarecord for the value document. The storage can be effected, for example,in such a way that respectively upon operation of the ultrasoundtransducers of one of the lines the ultrasound transmission values forthe ultrasound transducers of the respective line are successivelystored in a specified order, whereby corresponding to the alternateoperation of the ultrasound transducers of the lines the ultrasoundtransmission values of ultrasound transducers of the respectivelyoperated line are stored in the memory 50 after the ultrasoundtransmission values of ultrasound transducers of the line operatedrespectively before that. In particular, the ultrasound transmissionvalues can be stored as a vector whose index indicates the place forwhich a respective ultrasound transmission value was captured. The indexindicating the position in the vector then represents, together with theinstruction for the conversion of places or place coordinates into indexvalues, the place information. In the present embodiment example,ultrasound transmission values for N places on the respective valuedocument are captured for value documents of the specified valuedocument type.

The frequency with which the ultrasound pulses are successively emittedand the transport speed of the value document are chosen such that alongthe transport direction of the value document there are capturedultrasound transmission values in a distance of 3 mm, preferably 2 mm,along the transport direction or fifty or more transmission values.

In the present embodiment example of a method for checking valuedocuments of a specified value document type for the presence of atleast one irregularity in the form of at least one adhesion or a crease,the ultrasound transmission values are employed to check a respectivevalue document for whether it has an irregularity in the form of anadhesion or a crease. There is thus effected a check for the presence ofan irregularity of at least one specified type, the specified typesbeing adhesions and creases. If such an adhesion or crease isrecognized, the value document is associated with the state class “unfitfor circulation”. The adhesion here is an oblong adhesive strip which isaffixed at least on one side to the value document and adheres thereto.This is illustrated in FIG. 4, which shows a value document 60 of aspecified value document type with a watermark 62 represented in dots, asecurity thread 64 and an adhesive strip 66 marked by hatching.

The watermark 62, the security thread 64 and the adhesive strip 66, butalso a crease lead to changes in the ultrasound transmission incomparison to the other regions of the value document which are formedfrom a substrate of substantially constant thickness and density. Inparticular, adhesive strips reduce the ultrasound transmission. Thewatermark, however, increases the ultrasound transmission on account ofthe partially reduced weight per unit area. The exact position andconfiguration of the watermark 62 and the exact position of the securitythread 64 on the respective value document are not exactly constant forvalue documents of the specified value document type, but my varysubstantially within specified regions for different value documents ofthe specified type. This may impede the recognition of adhesive strips.

In the method there is employed a model for the location dependence ofthe ultrasound transmission of the value documents of the specifiedvalue document without adhesions, creases or damages, for example tearsor holes. The model defines model data records which lie within aspecified partial region of an N-dimensional space of possibleultrasound data. N is here the number of the places for which theultrasound property was captured and hence the number of the measurementresults of the ultrasound data record. This model may be ascertained asfollows:

First, reference value documents of the specified value document typewithout adhesions, creases or damages are specified. Preferably, thenumber of reference value documents is higher than 100.

For these reference value documents 44 there are captured, by means ofthe transmission ultrasound sensor, reference ultrasound data recordswhich describe in locally resolved fashion the ultrasound transmissionof the reference value documents for ultrasound of the ultrasound sensor44.

For this purpose, the ultrasound data records may be regarded as vectorswhose index reproduces the place at which the ultrasound transmissionvalue corresponding to the index was captured.

For fixing the partial region, the model data records may be representedby a sum of a mean vector and a linear combination of partial-regionvectors. A mean vector and unit vectors e_(j) orthogonal to each otherwith N components or of the dimension N are now ascertained, whichdescribe the reference ultrasound data records as well as possible. Thenumber K of the unit vectors is smaller than N and is chosen independence on the available computing capacity and the still acceptableerror as well as the number of the available reference ultrasound datarecords. The index j assumes integer values from 1 to K. The referencevalue documents, for the following representation, are designated withan index i running from 1 to the number M of the reference valuedocuments.

In the following, x_(i) designates the N-dimensional vector representingthe reference ultrasound data record for the reference value document i;as a mean vector the mean value of x_(i) over the reference valuedocuments is employed and designated as an N-dimensional vector m:

$m = {\frac{1}{M}{\sum\limits_{i}x_{i}}}$

An approximation y_(i) for a reference ultrasound data record x_(i),again representable as an N-dimensional vector, is then represented as asum of the mean vector or a mean value m and a linear combination of theunit vectors e_(j) with scalar coefficients a_(ij):

$y_{i} = {m + {\sum\limits_{j = 1}^{K}\; {a_{ij}e_{j}}}}$

By a suitable choice of the coefficients a_(ij) and of e_(j), the errorE between the approximations and the reference ultrasound data records

$E = {\sum\limits_{i = 1}^{M}\; \left. ||{y_{i} - x_{i}} \right.||^{2}}$

is to be minimized, for which purpose known optimization methods withLagrange multipliers may be employed.

The solution for the choice of the unit vectors e_(j) is given by the Knormalized eigenvectors v_(j) for the greatest eigen-values of thescattering or covariance matrix Σ

$\Sigma = {\frac{1}{M - 1}{\sum\limits_{i = 1}^{M}\; {\left( {x_{i} - m} \right)\left( {x_{i} - m} \right)^{T}}}}$

The superscript T designates here the transposed vector or further belowin connection with matrices the transposed matrix, x_(i) and m arecolumn vectors. The factor 1/(M−1) is irrelevant in the following andcan then be omitted.

K is chosen here preferably such that the error E is smaller than aspecified value.

The model obtained in this way hence defines model ultrasound datarecords z which are defined by the sum of the mean value vector m and alinear combination of the normalized eigenvectors v_(j):

$z = {m + {\sum\limits_{j = 1}^{K}\; {s_{j}v_{j}}}}$

s_(j) being scalar coefficients. The vectors z are vectors in theN-dimensional space.

This model is hence a model for the location dependence of theultrasound transmission of reference value documents of the specifiedvalue document type without irregularities in the form of adhesivestrips or creases.

For a captured ultrasound data record represented by the vector x, thebest approximation can be determined through the model or the minimaldeviation from the model, by minimizing, through adapting thecoefficients s_(j), the errors between the vector x and the model datarecords given by the set of possible vectors z. The specified deviationmeasure for the deviation between the ultrasound data record and a modeldata record is given by the norm of the difference between theultrasound data record and the model data record, the norm of a vectorbeing the root of the sum of the squares of the vector components.

If B designates the matrix (v₁ . . . , v_(k)), the K-dimensional vectorwill be ŝ′=(ŝ₁ . . . , ŝ_(k))^(T) of the coefficients of the linearcombination

ŝ=B ^(T)(x−m),  (1)

i.e. the model data record with the minimal deviation from theultrasound data record x is given by

z=m+Σ _(j=1) ^(K) ŝ _(j) v _(j).  (2)

The deviation data record is given by the deviation vector

R=x−(m+Bŝ)=x−[m+BB ^(T)(x−m)]  (3)

For the calculation of the deviation data record there are hence onlyrequired the components of the mean value vector m and that of thematrix B·B^(T) which must be ascertained and stored for a given valuedocument type.

For checking whether an indication of an irregularity in the form of atleast one adhesion, in particular an adhesive strip, or at least onecrease is present on the value document, features are ascertained independence on the deviation data record.

The following features are employed in this embodiment example:

The first feature M⁽¹⁾ relates to or describes the quantity of thedeviation described by the deviation data record. More precisely, thisembodiment example is given the feature by the Euclidean or L2 norm ofthe vector representing the deviation data record

M ⁽¹⁾ =∥R∥ ₂.

The second feature M⁽²⁾ represents a measure for the magnitude of thedeviations at places at which a difference between ultrasoundtransmission and model ascertainable from the deviation data of thedeviation data record indicates an irregularity in the form of anadhesion or crease. As an adhesion or crease reduces the ultrasoundtransmission, for a place with an adhesion or crease the deviation orthe deviation datum of the deviation data record is smaller than zero.The feature is given by

${M^{(2)} = {\sum\limits_{n = 1}^{N}\; {R_{n}{\Theta \left( {- R_{n}} \right)}}}},$

Θ(t) being the Heaviside function, i.e. Θ(t)=0 for t<0, 1 for theothers.

The third feature M⁽³⁾ represents a measure for places, for which thedeviation data of the deviation data record indicate an irregularity inthe form of an adhesion or crease, occurring spatially cumulated, themeasure also taking into account the quantities of the deviations. Anenergy function is employed here, which comprises a sum of contributionswhich respectively include products of deviation data at differentplaces, weighted with a weighting factor depending on the distance ofthe places; here, preferably only deviation data are taken into accountwhich indicate an irregularity in the form of at least one adhesion,preferably an adhesive strip, or at least one crease. More precisely,the Ising energy is employed for places with a reduced ultrasoundtransmission with an interaction with the next eight neighbors:

${M^{(3)} = {\sum\limits_{n,{m = 1},{n \neq m}}^{N}\; {w_{nm}{\theta \left( {- R_{n}} \right)}{\theta \left( {- R_{m}} \right)}R_{n}R_{m}}}},$

wherein w_(nm)=1 when the places corresponding to n and m are nearestneighbors, w_(nm)=1/√{square root over (2)}, when the placescorresponding to n and m are next but one or next nearest neighbors, andw_(nm)=0 for the others.

The fourth feature M⁽⁴⁾ represents a measure for the presence ofdeviations which indicate an irregularity in the form of at least oneadhesion or crease, along a line of a specified form, in the example astraight line. In this embodiment example, for this purpose, a Houghtransformation is carried out for those places whose deviation data ofthe deviation data record indicate an irregularity in the form of anadhesion or crease, hence are negative here. In the Hough transformationfor the recognition of straight lines, parameter pairs which define astraight line in the space of the places are ascertained for possiblestraight lines between two of the examined places in each case. Theregion of possible value pairs for the parameter pairs is divided intocells of a specified size, which respectively have associated therewitha counter. If a parameter pair falls in one of the cells, the valuethereof is incremented by one. As a feature there is now employed themaximum counter value, ascertained from all the cells, normalized withthe number of the places employed upon the transformation.

Upon checking whether an indication of an irregularity in the form of atleast one adhesion, in particular an adhesive strip, or a crease ispresent on the value document, a classification based on the features iscarried out by means of a support vector machine with non-linear core orkernel function. For training there are employed training valuedocuments of the specified value document type in a specifiedorientation, which have no irregularities have in the form of at leastone adhesion, in particular an adhesive strip, or a crease, and thosewhich have this one of one of these irregularities. The number oftraining value documents be L.

In the following, C or C₁ shall designate a vector formed of the featurevalues of the mentioned features for a captured ultrasound data record xor a reference ultrasound data record x_(l), whereby the index 1 may runfrom 1 to L. For this purpose, a distance function f is employed, whichis given by

${f(C)} = {{\sum\limits_{l = 1}^{L}\; {\alpha_{l}{k\left( {C,C_{l}} \right)}}} + {b.}}$

The decision function, which may assume the values +1 and −1, is thengiven by

c(C)=sign(f(C)).

The sign(t) is here a function, which is 1 if t≧0 and −1 for the others.The coefficients α₁ and the constant b may be ascertained by solving asquare optimization problem.

In the present example, a core or kernel function k with radial basefunctions is employed:

k(C,C _(l))=exp(−∥C−C _(l)∥²/(2σ²)).

The parameter σ is to be chosen suitably here, where applicable bytrying.

The result of the classification is binary, i.e. it is only ascertainedwhether or not an indication of an irregularity in the form of anadhesive strip or a crease is present (f(C)=1) or not (f(C)=−1).

The above-mentioned values and parameters are stored in the memory 52for each value document type which can be checked by means of theapparatus 10.

FIG. 5 shows a first embodiment example of a method for checking a valuedocument of a specified value document type for the presence of at leastone irregularity in the form of at least one adhesion, here an adhesivestrip, or a crease. For carrying out the method, in the control andevaluation device 48, more precisely the memory 52 thereof, there isstored a computer program upon the execution of which the control andevaluation device 48, more precisely the processor 50, executes thefirst embodiment of the method.

In step S10 an ultrasound data record which describes in locallyresolved fashion an ultrasound property, in this example the ultrasoundtransmission, of the value document is captured by means of thetransmission ultrasound sensor 44 for a value document. The transmissionultrasound sensor 44 captures, as described hereinbefore, the ultrasoundtransmission for measuring dots on the value document and formsrespective measurement values which are associated with the ultrasounddata record. The ultrasound data record corresponds to the vector x. Themeasurement values or the ultrasound data record are captured by thecontrol and evaluation device 48.

Then the evaluation device 48 ascertains in step S12 on the basis of animage of the value document captured by means of the optical remissionsensor 40 the value document type and orientation thereof.

In step S14 the evaluation device 48 ascertains the deviation datarecord which is represented above by the vector R. This vector describesin locally resolved fashion a deviation between the ultrasound datarecord and the model data record and is ascertained such that thedeviation described thereby is minimal with respect to the model. Forthis purpose, only the right side of the equation (3) has to becalculated.

In step S16 the evaluation device 48 ascertains, for carrying out thecheck whether an indication of an irregularity in the form of at leastone adhesion, in particular an adhesive strip, or a crease is present onthe value document, the features M⁽¹⁾ to M⁽⁴⁾.

The evaluation device 48 employs the calculated features in step S18 tocheck whether an indication of an irregularity in the form of at leastone adhesion, in particular an adhesive strip, or a crease is present onthe value document. For this purpose, it employs the above-describedsupport vector machine. The result in this embodiment example is binary,i.e. the result is +1, if the classification yields a presence of anadhesive strip or a crease, otherwise 0. The evaluation device 48 storesa corresponding value.

In step S20 it then forms in dependence on the result of step S18 anindication signal indicating whether or not the check has yielded thepresence of an irregularity in the form of an adhesion, in this case anadhesive strip, or a crease.

The result or the indication signal is employed by the control andevaluation device 48 for ascertaining a sorting result in dependence onthe results of other checks, and to drive the transport device 18, moreprecisely their gates, so that the value document is transported into anoutput portion associated with the sorting result.

A second embodiment example in FIG. 6 differs from the first embodimentexample in FIG. 5 only in that the steps S16 to S20 are replaced bysteps S16′ to S20′. Accordingly, the control and evaluation device andthe computer program stored therein are amended.

The step S16′ differs from step S16 in that the second feature M⁽²⁾ isreplaced by a feature M⁽⁶⁾, on the one hand. The latter likewisedescribes a measure for the magnitude of the deviations at places atwhich a difference between ultrasound transmission and modelascertainable from the deviation data of the deviation data recordindicates an irregularity in the form of an adhesion or crease. Thefeature is given by

$M^{(6)} = {\sum\limits_{n = 1}^{N}\; {R_{n}^{2}{\Theta \left( {- R_{n}} \right)}}}$

On the other hand, step S16′ differs from step S16 in that a furtherfeature M⁽⁷⁾ is employed which describes a probability that the modeldata record, which corresponds to the deviation data record, occursaccording to the model. The model data record corresponding to thedeviation data record is that model data record for which the deviationfrom the model is minimal.

For this purpose, in this embodiment example it is assumed that theultrasound data records are normally distributed in well enoughapproximation. As a parameter of the distribution the mean value and thecovariance matrix are ascertained. This is effected analogously to thefirst embodiment example, whereby as the mean value there is ascertainedthe mean vector and as the covariance matrix the above-mentionedcovariance matrix Σ. By a main component analysis of the distributionone reaches the model described above, which is supplemented by thestatement of a probability that a value document of the specified valuedocument type without an irregularity in the form of an adhesion, in theexample an adhesive strip, or crease has a model ultrasound data recordaccording to the equations (1) and (2) as the best approximation. Thelogarithm of the probability for the occurrence of a model data recordis then given by

$z = {m + {\sum\limits_{j = 1}^{K}\; {s_{j}v_{j}}}}$

${\log \left( {p\left( s \middle| {{error} - {free}} \right)} \right)} = {\log \left\lbrack \left( {2\pi} \right)^{- \frac{K}{2}} \middle| \Sigma_{s} \middle| {}_{- \frac{1}{2}}{\exp \left( {{- \frac{1}{2}}s^{T}\Sigma_{s}^{- 1}s} \right)} \right\rbrack}$

with the diagonal matrix

$\Sigma_{s} = \begin{pmatrix}\lambda_{1} & \ldots & 0 \\\vdots & \ddots & \vdots \\0 & \ldots & \lambda_{K}\end{pmatrix}$

of the K greatest eigen-values of the covariance matrix Σ. As a featureM⁽⁷⁾ then the logarithm of the probability that the model data recordoccurs with the minimal deviation from the ultrasound data recordaccording to the equations (1) and (2)

$M^{(7)} = {{\log \left( {p\left( \hat{s} \middle| {{error} - {free}} \right)} \right)} = {\log \left\lbrack \left( {2\pi} \right)^{- \frac{K}{2}} \middle| \Sigma_{s} \middle| {}_{- \frac{1}{2}}{\exp \left( {{- \frac{1}{2}}{\hat{s}}^{T}\Sigma_{s}^{- 1}\hat{s}} \right)} \right\rbrack}}$

is employed.

Already because of the different features, step S18 is replaced by stepS18′. The support vector machine and their parameters are replaced usingthe reference ultrasound data records analogous to the support vectormachine of the first embodiment example.

Accordingly, an indication signal which represents the value obtained instep S18′ is formed in step S20′.

A third embodiment example illustrated in FIG. 7 differs from the firstembodiment example in that the step S18 and accordingly the step S20 arereplaced by the steps S18″ and S20″. More precisely, in step S18 theaccordingly modified control and evaluation device 48 does not ascertaina classification result in the form of one of two classes as a result;upon checking it ascertains as a result a probability that for thespecified ultrasound data record an irregularity in the form of anadhesion, preferably an adhesive strip, or a crease was ascertained.

This is a probability that a class, which upon the classification wasobtained using the support vector machine, is appropriate for the givenultrasound data record, in particular for example that an adhesive stripor a crease is present when the ultrasound data record is given. Thisvalue is stored, as in the first embodiment example.

For this, in the present embodiment example there is employed thefollowing relation (cf. Platt, John C., “Probabilistic Outputs forSupport Vector Machines and Comparisons to Regularized LikelihoodMethods”, Advances in Large Margin Classifiers, 1999, pages 61 to 74):

${p\left( {c = \left. 1 \middle| x \right.} \right)} = {\frac{1}{1 + {\exp \left( {{{Af}(x)} + B} \right)}}.}$

The parameters A and B required therefor may be ascertained like theparameters for the support vector machine and be stored in the memory52.

A fourth embodiment example differs from the first embodiment example inthat the possible model data records are given by the mean value. Theformulae to be employed then result from the fact that the unit vectorsare omitted.

The fifth embodiment example differs from the above-described embodimentexamples in that instead of the feature M⁽³⁾ there is employed a featureM⁽⁸⁾ which also relates to a measure for places, for which the deviationdata of the deviation data record indicate an irregularity in the formof an adhesion or a crease, occurring spatially cumulated. For thispurpose, the control and evaluation device carries out, afterascertaining the deviation data which indicate an irregularity in theform of an adhesion or crease and hence are negative here, a blobanalysis for these ascertained deviation data. A blob designates here aset of places which form a coherent area and whose deviation dataindicate an irregularity in the form of an adhesion or crease.

As a feature M⁽⁸⁾ there is then employed the number of places in thegreatest ascertained set.

In developments of this embodiment example, as a further feature therecan be ascertained a measure for the places in the ascertained sets orblobs respectively lying within a form enclosing the places as close aspossible, in the example a parallelogram. For this, the relation of thenumber of places of the respective blob and the area of theparallelogram or rectangle may be employed as a feature.

Yet a further embodiment example differs from the above-describedembodiment examples in that before the ascertainment of the deviationdata record it is checked by the control and evaluation device whetherultrasound data of the ultrasound data record correspond to problemregions of the value document, for example to holes, tears or dog-ears.In the case of dog ears, the problem region comprises, on the one hand,the portion from which the corner of the value document corresponding tothe dog-ear was folded out, and on the other hand, the portion overwhich the corner was laid by folding.

For this, there may be employed an image of the optical remission sensoror preferably of the optical transmission sensor. Alternatively, theultrasound transmission data may be compared with a specified thresholdvalue. If a respective ultrasound transmission value exceeds thethreshold value for a place, this corresponds to a problem region orlies within this region.

If a place corresponds to a problem region or if a place lies within aproblem region, the ultrasound transmission value is replaced by areplacement transmission value specified for the place, which ischaracteristic for an intact value document of the specified valuedocument type. In the example, as a replacement transmission value thereis employed the ultrasound transmission value of the mean vector at thesame place. The other method steps are unchanged.

The described steps and features of the described embodiment examplesmay be exchanged or combined.

For ascertaining the ultrasound training data records, the followingmethod may be executed for generating ultrasound training data for theadaptation of parameters of a method for checking a value document of aspecified value document type for the presence of at least oneirregularity in the form of at least one adhesion, in the example anadhesive strip, or at least one crease. In the following the ultrasoundtraining data or ultrasound training data records are referred to onlyas training data or training data records, for simplicity's sake.

For the specified reference value documents which were employed forascertaining the model, ultrasound data records are captured whichrespectively describe in locally resolved fashion at least oneultrasound property, preferably the ultrasound transmission, of therespective reference value document. These are captured preferably withthe same ultrasound transmission sensor. These reference value documentsdo not have, as they were also employed for the adaptation of the model,an irregularity in the form of at least one adhesion or, here, anadhesive strip or a crease. These ultrasound data records are stored astraining data records. For each of these training data records furthertraining data records are now generated by means of a data processingdevice, which correspond to value documents of the specified valuedocument type having at least one irregularity in the form of anadhering adhesive strip or a crease.

The places for changes are given such that the form and/or position ofthe adhering adhesive strip or of the crease are chosen from a specifiedset of possible forms or positions. Further, the quantities of thechanges of the ultrasound transmission by the adhesive strip or thecrease are chosen from a specified region. For this, regions for thepossible lengths, widths and thicknesses of adhesive strips arespecified. Further, it is assumed that the adhesive strips may berandomly inclined relative to the edges of the respective value documentand offset relative to the edges. Further, the adhesive strips be of arectangular form, as long as they do not reach beyond the edge of thevalue document. In the latter case it is assumed that the adhesivestrips end on the edge of the value document.

Now, the orientation, i.e. position and inclination on the valuedocument, and the form, length and width, among other things, as well asthe thickness of the adhesive strip or the orientation and form of acrease are randomly chosen within the respectively given region. For theplaces given by the position and the form, the ultrasound data of theultrasound data record for the reference value document are then changedsuch that the change of the ultrasound transmission corresponds to asound intensity reduction or sound amplitude reduction by an adhesivestrip of the given thickness or a crease. The further training datarecords generated in this way are stored.

These training data records can then be employed instead of the trainingdata mentioned in the previous embodiment examples or in addition tothese.

Further embodiment examples differ from the above-described embodimentexamples in that instead of the check for an irregularity in the form ofat least one adhesion or crease there is carried out a check forirregularities in the form of material removals on value documentshaving a polymer layer which has an opaque cover applied thereon. Thefeature M⁽⁴⁾ is then not used. Further, the formulae for the featuresare to be adapted to that effect that a material removal leads to apositive deviation and not to a negative one.

Still further embodiment examples differ from the above-describedembodiment examples in that as an ultrasound property there is not usedthe ultrasound transmission but the ultrasound remission. Thetransmission ultrasound sensor is then replaced by a correspondingultrasound remission sensor. In this case an adhesion or creaseincreases the ultrasound remission, so that the method steps are to beadapted accordingly. A material removal, however, will reduce theultrasound remission, so that the method steps are to be adaptedaccordingly.

1-23. (canceled)
 24. A method for checking a value document of aspecified value document type for the presence of at least oneirregularity of at least one specified type, in which an ultrasound datarecord is captured, which describes in locally resolved fashion at leastone ultrasound property, of the value document; a deviation data recordis ascertained, which describes in locally resolved fashion a deviationbetween the ultrasound data record and a model and is ascertained suchthat the deviation described thereby is minimal with respect to themodel, wherein the model comprises a model for the location dependenceof the at least one ultrasound property of reference value documents ofthe specified value document type without irregularities of the at leastone specified type; and using the deviation data record, it is checkedwhether an indication of an irregularity of the at least one specifiedtype is present on the value document.
 25. The method according to claim24, in which the model defines a plurality of model data recordsdiffering from each other, which describe the at least one ultrasoundproperty in location-dependent fashion.
 26. The method according toclaim 25, in which the ultrasound data records respectively includeultrasound data for a number N of places which is specified for thevalue document type, which data respectively describe the at least oneultrasound property for the respective places, and in which the modeldata records respectively include model data for the at least oneultrasound property for the specified number N of places and lie in aspecified partial region of an N-dimensional space of possibleultrasound data.
 27. The method according to claim 26, in which thepartial region is specified such that model data records arerepresentable, upon a representation of the ultrasound data record andthe model data records as vectors of the same dimension, by a sum of amean vector and a linear combination of at least five specifiedpartial-region vectors.
 28. The method according to claim 27, in whichthe mean vector and the partial-region vectors are obtainable, orobtained by analysis of reference ultrasound data records for specifiedreference value documents of the specified value document type withoutirregularities of the at least one specified type.
 29. The methodaccording to claim 28, in which the analysis comprises a main componentanalysis, wherein the mean value ascertained upon the main componentanalysis corresponds to the mean vector and the main componentsascertained upon the main component analysis correspond to thepartial-region vectors.
 30. The method according to claim 25, in whichthe model has a statistical model distribution which describes aprobability of the occurrence of model data records.
 31. The methodaccording to claim 25, in which at least one feature is ascertained forthe deviation data record, and upon checking whether an indication of anirregularity of the at least one specified type is present on the valuedocument the at least one feature is employed, or in which at least twofeatures are ascertained for the deviation data record, and uponchecking whether an indication of an irregularity of the at least onespecified type is present on the value document the at least twofeatures are employed.
 32. The method according to claim 30, in which atleast one feature is ascertained for the deviation data record, and uponchecking whether an indication of an irregularity of the at least onespecified type is present on the value document the at least one featureis employed, or in which at least two features are ascertained for thedeviation data record, and upon checking whether an indication of anirregularity of the at least one specified type is present on the valuedocument the at least two features are employed.
 33. The methodaccording to claim 31, in which the feature or one of the featuresdescribes a probability that the ultrasound data record or the deviationdata record or the model data record corresponding to the deviation datarecord occurs according to the model.
 34. The method according to claim31, in which the feature or one of the features describes the quantityof the deviation described by the deviation data record.
 35. The methodaccording to claim 31, in which the feature or one of the featuresrepresents a measure for the magnitude of the deviations at places atwhich a difference between ultrasound transmission and model,ascertainable from the deviation data of the deviation data record,indicates an irregularity of the at least one specified type.
 36. Themethod according to claim 31, in which the feature or one of thefeatures represents a measure of places, for which the deviation data ofthe deviation data record indicate an irregularity of the at least onespecified type, occurring spatially cumulated, and that upon theascertainment of the measure also the quantities of the deviations aretaken into account.
 37. The method according to claim 31, in which thefeature or one of the features represents a measure for the presence ofdeviations at places for which the deviation data of the deviation datarecord indicate an irregularity of the at least one specified type,along a line of a specified form.
 38. The method according to claim 31,in which upon checking whether an indication of an irregularity of theat least one specified type is present on the value document aclassification is carried out by means of a support vector machine,using the at least one feature or the features.
 39. The method accordingto claim 32, in which upon checking whether an indication of anirregularity of the at least one specified type is present on the valuedocument a classification is carried out by means of a support vectormachine, using the at least one feature or the features.
 40. The methodaccording to claim 24, in which irregularities of the at least onespecified type comprise irregularities of the type of an adhesion, andor irregularities of the crease type.
 41. The method according to claim24, in which irregularities of the at least one specified type compriseirregularities of the type of a material removal.
 42. An apparatus forchecking a value document of a specified value document type for thepresence of at least one irregularity of at least one specified type,having an evaluation device which is configured for executing a methodaccording to claim 24, and in particular for capturing an ultrasounddata record which describes in locally resolved fashion at least oneultrasound property, the ultrasound transmission, of the value document;ascertaining a deviation data record which describes in locally resolvedfashion a deviation between the ultrasound data record and a model andis ascertained such that the deviation described thereby is minimal withrespect to the model, wherein the model comprises a model for thelocation dependence of the at least one ultrasound property of referencevalue documents of the specified value document type withoutirregularities of the at least one specified type and defines aplurality of model data records differing from each other which describethe at least one ultrasound property in location-dependent fashion; andusing the deviation data record, checking whether an indication of atleast one irregularity of the at least one specified type is present onthe value document.
 43. The apparatus according to claim 42, whichfurther has an ultrasound sensor for the locally resolved measurement ofthe at least one ultrasound property of a value document and formationof an ultrasound data record for the value document, and in which theevaluation device is coupled to the ultrasound sensor via a signalconnection and is configured to capture an ultrasound data record of theultrasound sensor as an ultrasound data record.
 44. A computer programfor execution by means of a data processing device, which has programcode, upon the execution of which the data processing device executes amethod according to claim
 24. 45. A data carrier which is readable bymeans of a data processing device and on which a computer programaccording to claim 44 is stored.
 46. A method for generating ultrasoundtraining data for adapting parameters of a method for checking a valuedocument of a specified value document type for the presence of at leastone irregularity of at least one specified type, for adapting parametersof a method according to claim 24, in which for specified referencevalue documents of the specified value document type there are capturedultrasound data records which respectively describe in locally resolvedfashion at least one ultrasound property, the ultrasound transmission,of the respective reference value document, wherein the specifiedreference value documents do not have an irregularity of the at leastone specified type; at least some of the ultrasound data records arestored as ultrasound training data records; from at least some of theultrasound data records there are generated further ultrasound trainingdata records, by changing, for respectively given places, the ultrasounddata of the ultrasound data record in such a way that the changecorresponds to a given irregularity of the at least one specified type,and the further ultrasound training data records are stored; and whereinthe parameters of the checking method are adapted using the ultrasoundtraining data records.
 47. The method according to claim 46, in whichupon the generation of one of the further ultrasound training datarecords the places are respectively given such that the form and/or theposition of the irregularity of the specified type is chosen from aspecified set of possible forms or positions.
 48. The method accordingto claim 46, in which upon the generation of one of the furtherultrasound training data records or of the one of the further ultrasoundtraining data records, the quantity of the change by the irregularity ofthe specified type is chosen from a specified region or a specified set.